Generative AI from Basic to Advance End-to-End RAG With Llama 3.1, Langchain, FAISS and OLlama #ai #llm #llama #huggingface
End-to-End RAG With Llama 3.1, Langchain, FAISS and OLlama #ai #llm #llama #huggingface Transcript and Lesson Notes
End-to-End Retrieval-Augmented Generation (RAG) using Llama 3.1, LangChain, and FAISS combines state-of-the-art AI models with efficient similarity search and a robust framework to create advanced solutions for real-time
Quick Summary
End-to-End Retrieval-Augmented Generation (RAG) using Llama 3.1, LangChain, and FAISS combines state-of-the-art AI models with efficient similarity search and a robust framework to create advanced solutions for real-time
Key Takeaways
- Review the core idea: End-to-End Retrieval-Augmented Generation (RAG) using Llama 3.1, LangChain, and FAISS combines state-of-the-art AI models with efficient similarity search and a robust framework to create advanced solutions for real-time
- Understand how rag app fits into End-to-End RAG With Llama 3.1, Langchain, FAISS and OLlama #ai #llm #llama #huggingface.
- Understand how rag application fits into End-to-End RAG With Llama 3.1, Langchain, FAISS and OLlama #ai #llm #llama #huggingface.
- Understand how rag tutorial fits into End-to-End RAG With Llama 3.1, Langchain, FAISS and OLlama #ai #llm #llama #huggingface.
- Understand how rag system fits into End-to-End RAG With Llama 3.1, Langchain, FAISS and OLlama #ai #llm #llama #huggingface.
Key Concepts
Full Transcript
End-to-End Retrieval-Augmented Generation (RAG) using Llama 3.1, LangChain, and FAISS combines state-of-the-art AI models with efficient similarity search and a robust framework to create advanced solutions for real-time information retrieval and generation(RAG). #llm #embedding #ai #futureai #generativeai #genai #textgeneration #ragapp #langchain #programminglogic #python #chatbot #openai #gpt #rag #transformers #multiretriever #advancerag #faiss #huggingface Don't miss out; learn with me! P.S. Don't forget to like and subscribe for more AI content! Notebook Link: https://github.com/sunnysavita10/Generative-AI-Indepth-Basic-to-Advance/blob/main/RAG_with_LLAMA3_1.ipynb Complete GenAI Material: https://github.com/sunnysavita10/Generative-AI-Indepth-Basic-to-Advance Multimodel RAG Playlis: https://www.youtube.com/watch?v=7CXJWnHI05w&list=PLQxDHpeGU14D6dm0rmAXhdLeLYlX2zk7p&pp=gAQBiAQB RAG detailed Playlist: https://www.youtube.com/watch?v=wTVTkOb3SZc&list=PLQxDHpeGU14Blorx3Ps1eZJ4XvKET1_vx&pp=gAQBiAQB GenAI Foundation Playlist: https://www.youtube.com/watch?v=ajWheP8ZD70&list=PLQxDHpeGU14D7NiPgqxC9qhKkx4jMQcDk&pp=gAQBiAQB Google Form For Suggestion and Feedback : https://forms.gle/1Ut21yM2ednvpbS66 Connect with me on Social Media- LinkedIn : https://www.linkedin.com/in/sunny-savita/ One to One Call: https://topmate.io/sunny_savita10 GitHub : https://github.com/sunnysavita10 Telegram : https://t.me/aimldlds
Lesson FAQs
What is End-to-End RAG With Llama 3.1, Langchain, FAISS and OLlama #ai #llm #llama #huggingface about?
End-to-End Retrieval-Augmented Generation (RAG) using Llama 3.1, LangChain, and FAISS combines state-of-the-art AI models with efficient similarity search and a robust framework to create advanced solutions for real-time
What key concepts are covered in this lesson?
The lesson covers rag app, rag application, rag tutorial, rag system, multimodal ai.
What should I learn before End-to-End RAG With Llama 3.1, Langchain, FAISS and OLlama #ai #llm #llama #huggingface?
Review the previous lessons in Generative AI from Basic to Advance, then use the transcript and key concepts on this page to fill any gaps.
How can I practice after this lesson?
Practice by applying the main concepts: rag app, rag application, rag tutorial, rag system.
Does this lesson include a transcript?
Yes. The full transcript is visible on this page in indexable HTML sections.
Is this lesson free?
Yes. CourseHive lessons and courses are available to learn online for free.
Continue Learning
Continue this lesson in the app
Install CourseHive on Android or iOS to keep learning while you move.
